LAPSE:2023.14106
Published Article
LAPSE:2023.14106
White-Model Predictive Control for Balancing Energy Savings and Thermal Comfort
March 1, 2023
To save energy consumed by a building, utilizing optimal predictive control with model predictive control (MPC) makes the most of energy storage systems (ESSs) to reduce the electrical energy consumption of peak and heavy loads. This study evaluated MPC applicability in a multi-zone commercial building using the EnergyPlus model and conducted multi-objective optimization of thermal comfort and energy savings. As a result of the simulation, optimal ESS charging scenarios responded to the fluctuating electricity pricing system, and changing the peak load time reduced the electricity bill of the grid by 55% compared to the existing operating method. At the same time, room temperatures stayed within the thermal comfort range, and the Pareto curve showed a proper balance between energy saving and thermal comfort. Especially, the proposed method with a white model is applicable for MPC applications in commercial buildings, as it gave optimal solutions within the target time interval.
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Keywords
energy saving, Genetic Algorithm, Model Predictive Control, multi-objective optimization, thermal comfort
Subject
Suggested Citation
Jeon BK, Kim EJ. White-Model Predictive Control for Balancing Energy Savings and Thermal Comfort. (2023). LAPSE:2023.14106
Author Affiliations
Journal Name
Energies
Volume
15
Issue
7
First Page
2345
Year
2022
Publication Date
2022-03-23
Published Version
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en15072345, Publication Type: Journal Article
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LAPSE:2023.14106
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doi:10.3390/en15072345
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[v1] (Original Submission)
Mar 1, 2023
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Mar 1, 2023
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